TY - JOUR
T1 - Scour assessment for offshore wind turbines
T2 - a state-of-the-art review
AU - Feng, Xin
AU - Zheng, Jintong
AU - Liu, Yiming
AU - Bao, Yi
N1 - Publisher Copyright:
© Springer-Verlag GmbH Germany, part of Springer Nature 2025.
PY - 2025
Y1 - 2025
N2 - Offshore wind turbines (OWTs) are subject to waves, currents, seabed shifts, and corrosion in harsh marine environment, posing significant challenges to structural integrity and durability. A prevalent issue of OWTs is the scour of foundations and cables, which can cause structural damage, interrupting the operation of OWTs and even leading to catastrophic failure. Timely detection and assessment of scour are crucial for maintaining the structural integrity and managing the operation of OWTs. This paper reviews the main methods utilized to assess scour for OWT. Three main types of scour assessment methods are reviewed, which are direct methods, vibration-based methods, and unmanned vehicle-based methods. For each type of methods, the reviewed contents mainly include the assessment principles, laboratory tests, and field applications, as well as data processing and interpretation. The limitations of existing methods and the new opportunities are discussed. This research promotes improvement of the monitoring and maintenance of OWTs.
AB - Offshore wind turbines (OWTs) are subject to waves, currents, seabed shifts, and corrosion in harsh marine environment, posing significant challenges to structural integrity and durability. A prevalent issue of OWTs is the scour of foundations and cables, which can cause structural damage, interrupting the operation of OWTs and even leading to catastrophic failure. Timely detection and assessment of scour are crucial for maintaining the structural integrity and managing the operation of OWTs. This paper reviews the main methods utilized to assess scour for OWT. Three main types of scour assessment methods are reviewed, which are direct methods, vibration-based methods, and unmanned vehicle-based methods. For each type of methods, the reviewed contents mainly include the assessment principles, laboratory tests, and field applications, as well as data processing and interpretation. The limitations of existing methods and the new opportunities are discussed. This research promotes improvement of the monitoring and maintenance of OWTs.
KW - Digital twin
KW - Machine learning
KW - Offshore wind turbine (OWT)
KW - Scour
KW - Structural health monitoring (SHM)
KW - Unmanned vehicle
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U2 - 10.1007/s13349-025-00934-w
DO - 10.1007/s13349-025-00934-w
M3 - Article
AN - SCOPUS:105002345705
SN - 2190-5452
JO - Journal of Civil Structural Health Monitoring
JF - Journal of Civil Structural Health Monitoring
M1 - 112250
ER -